Field
The disclosed concept pertains generally to electric loads and, more particularly, to load power devices that power such loads. The disclosed concept also pertains to energy systems including load power devices that power electric loads.
Background Information
Power consumption monitoring and energy management of plug-in electric loads (PELs) inside buildings are often overlooked. By knowing the operating mode (e.g., operating status) of an electric load, energy savings can be achieved with effective management and control thereof. Also, operating mode and energy consumption of electric loads need to be communicated to building management systems in an automatic, low cost and non-intrusive manner.
Electric loads often present unique characteristics in outlet electric signals (i.e., voltage; current; power). Such load characteristics provide a viable mechanism to identify operating status (e.g., without limitation, active; standby) by analyzing the outlet electric signals.
Prior proposals include usage of wavelet coefficients obtained from wavelet transforms and event detection to detect switching of the load. Also, basic power quality related signatures (e.g., one or more of apparent power, cos (phi), active energy, reactive energy, frequency, period, RMS current, instantaneous current, RMS voltage, instantaneous voltage, current harmonic THD (total harmonic distortion) percentage, voltage harmonic THD percentage, spectral content of the current waveform, spectral content of the voltage waveform, spectral content of the active power waveform, spectral content of the reactive power waveform, quality of the network percentage, time, date, temperature, and humidity) are used as a signature to identify a load and its operating status.
For example, a load is in a standby mode when the current value obtained for each load current is less than a percentage of the maximum for each load current in the normal operating state. When an electric appliance plugged into a master socket consumes power less than a suitable threshold (e.g., that of standby power), then those peripheral sockets might be switched off automatically to cut further power consumption. While this may be true for some electric devices, other electric loads (e.g., without limitation, microwaves; refrigerators) have ON-OFF behavior which is a unique internal behavior of the electric load itself (e.g., a desktop computer low power mode). It is not user friendly if the “OFF” cycle of such a device is improperly considered to be a “standby” mode and such load is then turned OFF.
There are known challenges and constraints to make load identification algorithms execute in real-time. Implementation of load identification algorithms in real-time relies on the actual use status of loads and user-behavior. Not all of the information from every moment is useful for meaningful load identification. Hence, ensuring that different levels of load identification algorithms are enabled at the right moments is essential to obtaining accurate, reliable, and trustful performance.
As a challenging real-time system, reliable event detection and operating mode detection is key to ensuring that important power cycles are not missed during processing. It is believed that pre-acquiring and processing data would give false results. Since a complete load identification system has various levels of algorithms which need to be processed in real-time to generate desired results, the proper scheduling of corresponding tasks is also critical.
There is room for improvement in load power devices.
There is further room for improvement in energy systems including load power devices.